AGETS MBR An Application of Model-Based Reasoning to Gas Turbine Diagnostics
Winston, Howard A., Clark, Robert T., Buchina, Gene
A common difficulty in diagnosing failures within Pratt & Whitney's F100-PW-100/200 gas turbine engine occurs when a fault in one part of a system -- comprising an engine, an airframe, a test cell, and automated ground engine test set (AGETS) equipment -- is manifested as an out-of-bound parameter elsewhere in the system. In such cases, the normal procedure is to run AGETS self-diagnostics on the abnormal parameter. However, because the self-diagnostics only test the specified local parameter, it will pass, leaving only the operators' experience and traditional fault-isolation manuals to locate the source of the problem in another part of the system. This article describes a diagnostic tool (that is, AGETS MBR), designed to overcome this problem by isolating failures using an overall system troubleshooting approach. AGETS MBR was developed jointly by personnel at Pratt & Whitney and United Technologies Research Center using an AI tool called the qualitative reasoning system (QRS).
Dec-15-1995
- Country:
- North America > United States > Connecticut > Hartford County (0.14)
- Industry:
- Aerospace & Defense (1.00)
- Energy > Oil & Gas (0.70)
- Government > Military
- Air Force (0.50)
- Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning
- Diagnosis (1.00)
- Expert Systems (1.00)
- Model-Based Reasoning (1.00)
- Qualitative Reasoning (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning